Triple
T30279762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 28th Infantry Regiment |
E770053
|
entity |
| Predicate | resultAtAlligatorCreek |
P181335
|
FINISHED |
| Object | regiment largely destroyed |
—
|
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: regiment largely destroyed | Statement: [28th Infantry Regiment, resultAtAlligatorCreek, regiment largely destroyed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resultAtAlligatorCreek Context triple: [28th Infantry Regiment, resultAtAlligatorCreek, regiment largely destroyed]
-
A.
reachedRiver
Indicates that an entity has arrived at or come into contact with a river as a result of movement or travel.
-
B.
AlligatorAlleySectionRunsBetween
Indicates that a specific section of Alligator Alley extends between two specified locations or endpoints.
-
C.
locatedOnTributaryOf
Indicates that one entity is situated along or on the banks of a tributary that flows into another specified water body.
-
D.
hasOutletRiver
Indicates that a body of water discharges or flows out into a specified river as its outlet.
-
E.
hasRiverCrossingNearby
Indicates that there is a river crossing located in close proximity to the referenced entity or location.
- 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_69f224868fa8819099127eaf8855a28f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
| PDg | Predicate description generation | batch_69f7688cea58819098bdfd7c80df7634 |
completed | May 3, 2026, 3:23 p.m. |
Created at: April 29, 2026, 7:45 p.m.