Triple
T36298775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crow King |
E893444
|
entity |
| Predicate | facedUnit |
P185111
|
FINISHED |
| Object | 7th Cavalry Regiment (United States) |
—
|
NE NERFINISHED |
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: 7th Cavalry Regiment (United States) | Statement: [Crow King, facedUnit, 7th Cavalry Regiment (United States)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facedUnit Context triple: [Crow King, facedUnit, 7th Cavalry Regiment (United States)]
-
A.
facedBy
Indicates that one entity is oriented toward and directly opposite another entity, such that it is facing it.
-
B.
faceValueUnit
Indicates the unit of measurement in which the face value of something (such as a financial instrument or item) is expressed.
-
C.
formedUnit
Indicates that one entity has been organized or constituted into a specific unit or group, establishing a formal unit-level relationship between them.
-
D.
facedWeapon
Indicates that one entity confronted, opposed, or dealt with another entity while that other entity was armed with a weapon.
-
E.
facedChange
Indicates that an entity has encountered and had to deal with a modification, challenge, or transition affecting its prior state or circumstances.
- 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_69f76e4a61f0819084a2b68dbbb4efc6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb1d6b70819091227bd011734d19 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7ba6c27e081908868a2b50d1d603c |
completed | May 3, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:09 p.m.