Triple
T1894501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All American Division |
E41947
|
entity |
| Predicate | hasTypeHistory |
P32919
|
FINISHED |
| Object | infantry division |
—
|
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: infantry division | Statement: [All American Division, hasTypeHistory, infantry division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeHistory Context triple: [All American Division, hasTypeHistory, infantry division]
-
A.
hasPolicyHistory
Indicates that an entity is associated with a record or sequence of past policies that have applied to it over time.
-
B.
hasTransportHistoryAs
Indicates that an entity has a record or log of being transported, characterized or classified in a specific way.
-
C.
hasHistoricalEntity
Indicates a relationship where one entity includes, references, or is associated with another entity that existed or is defined in a past historical context.
-
D.
hasTransportHistory
Indicates that there exists a record or sequence of past transportation-related events or movements associated with an entity.
-
E.
includesChangeHistory
Indicates that the subject maintains or contains a record of past modifications or changes made to it.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1497df08190ad90dd89f76208ca |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe7e7e88190b58c0df59187c0c2 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb09b27e88190bff164040fef6d7e |
completed | March 7, 2026, 4:59 a.m. |
Created at: March 4, 2026, 7:34 p.m.