Triple
T37299495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 99th Infantry Division |
E925899
|
entity |
| Predicate | notableLocationOfAction |
P203901
|
FINISHED |
| Object | Elsenborn Ridge |
E9371
|
NE 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: Elsenborn Ridge | Statement: [99th Infantry Division, notableLocationOfAction, Elsenborn Ridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLocationOfAction Context triple: [99th Infantry Division, notableLocationOfAction, Elsenborn Ridge]
-
A.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
B.
notableGameLocation
Indicates that a particular place is recognized as a significant or prominent location within a game.
-
C.
notableLocationOn
chosen
Indicates that a particular location is especially significant or noteworthy in relation to a specified entity or context.
-
D.
notableAsSettingOf
Indicates that a place or environment is recognized as the setting where the events of a particular work (e.g., book, film, story) take place.
-
E.
notableFilmingLocation
Indicates that a place served as a significant or well-known location where a film or television production was shot.
- F. None of above.
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_69f76eb0f86c819098dee07393e69ec3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40638b0704819088facbbace0ca439 |
completed | June 27, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.