Triple
T2110294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Ysidro neighborhood of San Diego |
E42484
|
entity |
| Predicate | hasCommercialFeature |
P182
|
FINISHED |
| Object | outlet shopping centers |
—
|
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: outlet shopping centers | Statement: [San Ysidro neighborhood of San Diego, hasCommercialFeature, outlet shopping centers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialFeature Context triple: [San Ysidro neighborhood of San Diego, hasCommercialFeature, outlet shopping centers]
-
A.
hasCommercialFunction
Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
-
B.
hasBroadcastFeature
Indicates that an entity includes or supports a broadcast-related capability or functionality.
-
C.
hasFeature
chosen
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
D.
hasMIC
Indicates that an entity has a specified Minimum Inhibitory Concentration (MIC) value in relation to an antimicrobial agent.
-
E.
hasMP
Indicates that an entity is represented by, or associated with, a specific Member of Parliament (MP).
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb024ce88190a30e1320e53b82bc |
completed | March 7, 2026, 5:43 a.m. |
| PD | Predicate disambiguation | batch_69abb7ba08948190a3c236bb53ee4257 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.