Triple
T36580004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomás Romo |
E902364
|
entity |
| Predicate | primaryAudienceLocation |
P89961
|
FINISHED |
| Object | Mexico |
E346
|
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: Mexico | Statement: [Tomás Romo, primaryAudienceLocation, Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAudienceLocation Context triple: [Tomás Romo, primaryAudienceLocation, Mexico]
-
A.
locationOfAudience
chosen
Indicates the place or setting where the audience is situated or gathered.
-
B.
primaryLocationIn
Indicates that an entity’s main or most significant location is within or at the referenced place.
-
C.
primaryRegionOfPopularity
Indicates the geographic region where something is most widely used, favored, or popular compared to other regions.
-
D.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
-
E.
primaryLocationCity
Indicates the city that serves as the main or primary location associated with the subject.
- 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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a39f914994c81909a77fe6852d835ec |
completed | June 23, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.