Triple
T37572499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bisig Bayan |
E934725
|
entity |
| Predicate | locationOfStation |
P205988
|
FINISHED |
| Object | Quezon City |
E10123
|
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: Quezon City | Statement: [Bisig Bayan, locationOfStation, Quezon City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfStation Context triple: [Bisig Bayan, locationOfStation, Quezon City]
-
A.
locationOfParentStation
Indicates that one entity is the place where the parent or main station of another entity is situated.
-
B.
originalStationLocation
Indicates the location where a station was initially established or first situated.
-
C.
stationName
Indicates the name assigned to a particular station in the relationship.
-
D.
isStationOf
Indicates that a given location functions as a station (e.g., transport or service hub) associated with or serving a particular system, line, route, or organization.
-
E.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
- 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_69f76ecd99148190be327e391a70f5b6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40fb62b5a88190ba897880548a8629 |
completed | June 28, 2026, 10:45 a.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:17 p.m.