Triple
T31013708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tejeros, San Francisco de Malabon, Cavite, Philippines |
E790271
|
entity |
| Predicate | currentMunicipalityNameContext |
P11890
|
FINISHED |
| Object | General Trias |
E363936
|
NE FINISHED |
How this triple was built (2 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: General Trias | Statement: [Tejeros, San Francisco de Malabon, Cavite, Philippines, currentMunicipalityNameContext, General Trias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentMunicipalityNameContext Context triple: [Tejeros, San Francisco de Malabon, Cavite, Philippines, currentMunicipalityNameContext, General Trias]
-
A.
municipalityName
Indicates the official name assigned to a municipality.
-
B.
presentDayMunicipality
chosen
Indicates that one entity is the current-day municipality encompassing or corresponding to the area or jurisdiction of another (typically historical) entity.
-
C.
currentOfficialNameOfPlace
Indicates that the object is the official name currently in use for the referenced place.
-
D.
hasNameInMunicipality
Indicates that an entity is known by a particular name within the context or jurisdiction of a specific municipality.
-
E.
currentCityName
Indicates the name of the city where the entity is currently located.
- F. None of above.
Provenance (4 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a292b0460388190b90337daf8ddb32e |
completed | June 10, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: April 29, 2026, 8:57 p.m.