Triple
T36102334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alison McCord |
E1044246
|
entity |
| Predicate | countryOfCitizenshipInStory |
P2
|
FINISHED |
| Object | United States |
E14
|
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: United States | Statement: [Alison McCord, countryOfCitizenshipInStory, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfCitizenshipInStory Context triple: [Alison McCord, countryOfCitizenshipInStory, United States]
-
A.
countryOfCitizenship
chosen
Indicates the country in which a person or entity holds legal citizenship.
-
B.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
C.
creatorCountryOfCitizenship
Indicates the country in which the creator holds or held legal citizenship.
-
D.
cityOfCitizenship
Indicates the city in which a person holds legal citizenship or official civic affiliation.
-
E.
possibleCountryOfCitizenship
Indicates that an entity could plausibly be a country in which the person or agent may hold, or be eligible to hold, citizenship.
- 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_69f76e338e2c8190b7f3bc68bec76349 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0238010fa481909b07a5c22aa0abde |
completed | May 11, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38d5247cc88190bd87a8fa366c0bf7 |
completed | June 22, 2026, 6:24 a.m. |
| PD | Predicate disambiguation | batch_6a0236cfdcb481908323b67b925c76d9 |
completed | May 11, 2026, 8:06 p.m. |
Created at: May 3, 2026, 4:08 p.m.