Triple
T11963158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ortigas MRT station |
E284720
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
Ortigas
Ortigas is a busy elevated station on Manila’s MRT Line 3 serving the Ortigas Center business district in Metro Manila, Philippines.
|
E956970
|
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: Ortigas | Statement: [Ortigas MRT station, hasStationCode, Ortigas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ortigas Context triple: [Ortigas MRT station, hasStationCode, Ortigas]
-
A.
Benincasa
Benincasa is an Italian surname historically associated with the family of the medieval mystic and saint Catherine of Siena.
-
B.
Asparros
Asparros was a military commander known for leading forces in the Battle of Pamplona.
-
C.
Segeda
Segeda was a prominent ancient Celtiberian city in what is now northeastern Spain, known for its role in the Celtiberian Wars against Rome.
-
D.
Harroz
Harroz is the surname of Joseph Harroz Jr., an American academic administrator and president of the University of Oklahoma.
-
E.
Verdolagas
Verdolagas is the popular nickname of Honduran football club Marathón, one of the country’s most traditional and successful teams.
- 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: Ortigas Triple: [Ortigas MRT station, hasStationCode, Ortigas]
Generated description
Ortigas is a busy elevated station on Manila’s MRT Line 3 serving the Ortigas Center business district in Metro Manila, Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ortigas Target entity description: Ortigas is a busy elevated station on Manila’s MRT Line 3 serving the Ortigas Center business district in Metro Manila, Philippines.
-
A.
Benincasa
Benincasa is an Italian surname historically associated with the family of the medieval mystic and saint Catherine of Siena.
-
B.
Asparros
Asparros was a military commander known for leading forces in the Battle of Pamplona.
-
C.
Segeda
Segeda was a prominent ancient Celtiberian city in what is now northeastern Spain, known for its role in the Celtiberian Wars against Rome.
-
D.
Harroz
Harroz is the surname of Joseph Harroz Jr., an American academic administrator and president of the University of Oklahoma.
-
E.
Verdolagas
Verdolagas is the popular nickname of Honduran football club Marathón, one of the country’s most traditional and successful teams.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037848f481908276716675464464 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4594054f08190b28b35f62dfb9198 |
completed | May 1, 2026, 7:41 a.m. |
| NEDg | Description generation | batch_69f45f89d5b08190a87312d96e61898a |
completed | May 1, 2026, 8:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f464a5191881908e291943996169cb |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 8, 2026, 9:45 p.m.