Triple
T12641235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayala station |
E301901
|
entity |
| Predicate | hasCommercialAccess |
P105471
|
FINISHED |
| Object | shopping malls |
—
|
LITERAL 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: shopping malls | Statement: [Ayala station, hasCommercialAccess, shopping malls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialAccess Context triple: [Ayala station, hasCommercialAccess, shopping malls]
-
A.
hasCommercialServices
chosen
Indicates that one entity provides or offers commercial services to another entity or within a specified context.
-
B.
hasCommercialAxis
Indicates that there exists a primary direction, route, or area along which commercial or business activities are concentrated or organized.
-
C.
hasCommercialField
Indicates that one entity possesses or is associated with a commercial-related field, area, or domain in relation to another entity.
-
D.
hasCommercialFunction
Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
-
E.
supportsCommercialFlights
Indicates that the subject provides the necessary facilities, services, or conditions for regular commercial passenger or cargo flights to operate.
- F. None of above.
Provenance (3 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:17 p.m.