Triple
T27605535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas politicians |
E700168
|
entity |
| Predicate | includesDemographic |
P114768
|
FINISHED |
| Object | Anglo-American politicians |
—
|
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: Anglo-American politicians | Statement: [Texas politicians, includesDemographic, Anglo-American politicians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesDemographic Context triple: [Texas politicians, includesDemographic, Anglo-American politicians]
-
A.
hasDemographic
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
B.
involvesDemographic
Indicates that an action, event, or entity is related to, affects, or includes a specific demographic group or population segment.
-
C.
hasDemographicPresenceIn
chosen
Indicates that a particular demographic group exists or is represented within a specified geographic area or population context.
-
D.
demographicsIn
Indicates that demographic information is associated with or applies within a specified geographic or organizational area.
-
E.
hasDemographicUnit
Indicates that an entity is associated with or contains a specific demographic unit (such as a population group or segment).
- 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_69ef6a4e2e208190b63b7268f405785c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69fe1fd637c08190aa95cd2478c278cb |
completed | May 8, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69fe19344bb481909b5e2144155e4add |
completed | May 8, 2026, 5:11 p.m. |
Created at: April 27, 2026, 2:09 p.m.