Triple
T140310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gettysburg Address |
E2835
|
entity |
| Predicate | locationType |
P3024
|
FINISHED |
| Object | battlefield cemetery dedication |
—
|
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: battlefield cemetery dedication | Statement: [Gettysburg Address, locationType, battlefield cemetery dedication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationType Context triple: [Gettysburg Address, locationType, battlefield cemetery dedication]
-
A.
locationDescription
chosen
Indicates a textual description that specifies or characterizes the location of an entity.
-
B.
locationVariesWith
Indicates that the location of one entity changes in dependence on, or as a function of, changes in another entity.
-
C.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
D.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
E.
locatedAlong
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257c679d88190bc71775dab2cfc64 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.