Triple
T37329898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oglethorpe, Texas |
E926714
|
entity |
| Predicate | drinkingAgeLegal |
P104596
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [Oglethorpe, Texas, drinkingAgeLegal, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drinkingAgeLegal Context triple: [Oglethorpe, Texas, drinkingAgeLegal, 21]
-
A.
drinksLegalAge
Indicates that an entity has reached the minimum legal age required to consume alcoholic beverages.
-
B.
legalAgeToPurchase
Indicates that an entity has reached the minimum legally permitted age to purchase a specified item or service.
-
C.
drinkingPermitted
Indicates that consuming alcoholic beverages is allowed in a given context, location, or situation.
-
D.
minimumAlcoholRegulated
chosen
Indicates that there is a legally or formally established minimum alcohol-related threshold (such as age, content, or quantity) that is subject to regulation.
-
E.
alcoholRange
Indicates the range or interval of alcohol content associated with an entity (e.g., minimum and maximum alcohol level).
- 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_69f76eb386d88190a8d511aa11540dfc |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:16 p.m.