Triple
T15475968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Safety Harbor site |
E376780
|
entity |
| Predicate | locatedWithin |
P40
|
FINISHED |
| Object |
Philippe Park
Philippe Park is a historic waterfront park in Safety Harbor, Florida, known for its Native American temple mound, scenic views of Old Tampa Bay, and recreational amenities.
|
E1159342
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Philippe Park | Statement: [Safety Harbor site, locatedWithin, Philippe Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philippe Park Context triple: [Safety Harbor site, locatedWithin, Philippe Park]
-
A.
Philippe Maystadt
Philippe Maystadt was a Belgian politician and economist who served as Belgium’s Minister of Finance and later as president of the European Investment Bank.
-
B.
Philippe Clay
Philippe Clay was a French actor and singer known for his tall, lanky silhouette and distinctive performances in mid-20th-century French cinema and cabaret.
-
C.
Philippe Leonelli
Philippe Leonelli is a French local politician who serves as the mayor of the Mediterranean coastal town of Cavalaire-sur-Mer.
-
D.
Philippe Martin
Philippe Martin is a French film producer known for his work on acclaimed European cinema.
-
E.
Philippe Martin
Philippe Martin is the central protagonist of the romantic drama film "When Tomorrow Comes."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Philippe Park Triple: [Safety Harbor site, locatedWithin, Philippe Park]
Generated description
Philippe Park is a historic waterfront park in Safety Harbor, Florida, known for its Native American temple mound, scenic views of Old Tampa Bay, and recreational amenities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Philippe Park Target entity description: Philippe Park is a historic waterfront park in Safety Harbor, Florida, known for its Native American temple mound, scenic views of Old Tampa Bay, and recreational amenities.
-
A.
Philippe Maystadt
Philippe Maystadt was a Belgian politician and economist who served as Belgium’s Minister of Finance and later as president of the European Investment Bank.
-
B.
Philippe Clay
Philippe Clay was a French actor and singer known for his tall, lanky silhouette and distinctive performances in mid-20th-century French cinema and cabaret.
-
C.
Philippe Leonelli
Philippe Leonelli is a French local politician who serves as the mayor of the Mediterranean coastal town of Cavalaire-sur-Mer.
-
D.
Philippe Martin
Philippe Martin is a French film producer known for his work on acclaimed European cinema.
-
E.
Philippe Martin
Philippe Martin is the central protagonist of the romantic drama film "When Tomorrow Comes."
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f88a5dc8190a2d7830748e29180 |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2d093ccc8190aefc355a837c83f4 |
completed | May 9, 2026, 12:48 p.m. |
| NEDg | Description generation | batch_69ff3015ee2c8190ad2c28cd2850d903 |
completed | May 9, 2026, 1:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff30ed9a5481909cefad0ef877a2e9 |
completed | May 9, 2026, 1:04 p.m. |
Created at: April 10, 2026, 3:34 a.m.