Triple
T2137578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Carter |
E46689
|
entity |
| Predicate | testCaps |
P37001
|
FINISHED |
| Object | 112 |
—
|
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: 112 | Statement: [Dan Carter, testCaps, 112]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: testCaps Context triple: [Dan Carter, testCaps, 112]
-
A.
mostCaps
Indicates that the subject entity possesses the greatest number of capital letters (or capitalized elements) compared to a specified set of entities.
-
B.
caps
Indicates that one entity serves as the capital city or administrative center of another entity, such as a country, state, or region.
-
C.
hasCapitalFunction
Indicates that an entity serves as the primary seat of government or main administrative center for another entity.
-
D.
displayCapabilities
Indicates the set of functions, features, or behaviors that an entity is able to present or support in a given context.
-
E.
capitalizedOn
Indicates that one entity took advantage of, exploited, or made beneficial use of an opportunity, situation, or resource provided or created by another entity.
- F. None of above. chosen
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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbf74147c81908793c3694894f94a |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbd96a3b0819081efbfef975e1513 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbf71edf08190add69022aabfd49d |
completed | March 7, 2026, 6:02 a.m. |
Created at: March 4, 2026, 7:44 p.m.