Triple
T5446986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Micks |
E122272
|
entity |
| Predicate | refersToUnitType |
P28425
|
FINISHED |
| Object | infantry regiment |
—
|
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 regiment | Statement: [The Micks, refersToUnitType, infantry regiment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToUnitType Context triple: [The Micks, refersToUnitType, infantry regiment]
-
A.
associatedUnitType
chosen
Indicates that one entity is linked to or characterized by a particular type or category of unit.
-
B.
basedUnitType
Indicates that one unit is defined or derived in terms of another underlying (base) unit type.
-
C.
typeOfUnit
Indicates that one entity specifies the kind or category of measurement unit that the other entity belongs to.
-
D.
typicalSupportedUnitType
Indicates the kind or category of unit that an entity is normally designed or expected to support.
-
E.
typicalUnitType
Indicates that one entity is the standard or commonly used unit type associated with measuring or expressing the other entity.
- 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_69bd4640f52c81909e653ec361f66d76 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:07 p.m.