Triple
T8738172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florence Halop |
E207436
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Halop
Halop is the surname of Florence Halop, an American actress best known for her roles on classic television sitcoms such as "Night Court."
|
E755753
|
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: Halop | Statement: [Florence Halop, familyName, Halop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halop Context triple: [Florence Halop, familyName, Halop]
-
A.
HAL
HAL is the vehicle registration code used on license plates for the German city of Halle (Saale).
-
B.
HAL
HAL is the ICAO airline designator used to identify Hawaiian Airlines in international aviation operations.
-
C.
HAL
HAL is an open-access multidisciplinary archive and repository for scholarly documents, widely used by researchers to share and preserve their scientific publications.
-
D.
HAL
HAL is the stock ticker symbol for Halliburton Company, a major American oilfield services and energy industry equipment provider.
-
E.
HAL
HAL is a major Indian state-owned aerospace and defense company that designs, manufactures, and maintains aircraft, helicopters, and related systems.
- 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: Halop Triple: [Florence Halop, familyName, Halop]
Generated description
Halop is the surname of Florence Halop, an American actress best known for her roles on classic television sitcoms such as "Night Court."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Halop Target entity description: Halop is the surname of Florence Halop, an American actress best known for her roles on classic television sitcoms such as "Night Court."
-
A.
HAL
HAL is the vehicle registration code used on license plates for the German city of Halle (Saale).
-
B.
HAL
HAL is the ICAO airline designator used to identify Hawaiian Airlines in international aviation operations.
-
C.
HAL
HAL is an open-access multidisciplinary archive and repository for scholarly documents, widely used by researchers to share and preserve their scientific publications.
-
D.
HAL
HAL is the stock ticker symbol for Halliburton Company, a major American oilfield services and energy industry equipment provider.
-
E.
HAL
HAL is a major Indian state-owned aerospace and defense company that designs, manufactures, and maintains aircraft, helicopters, and related systems.
- 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d470c8c81909ead395ef704c6ba |
completed | March 31, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf42c9140081909f9c10560757c860 |
completed | April 3, 2026, 4:32 a.m. |
| NEDg | Description generation | batch_69cf43ead588819094089bea94c27207 |
completed | April 3, 2026, 4:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf453fa3e4819082466c59649c2f35 |
completed | April 3, 2026, 4:42 a.m. |
Created at: March 30, 2026, 6:38 p.m.