Triple
T11615585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dennison Railroad Depot Museum |
E275495
|
entity |
| Predicate | numberOfTroopsServedEstimate |
P6153
|
FINISHED |
| Object | 1300000 |
—
|
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: 1300000 | Statement: [Dennison Railroad Depot Museum, numberOfTroopsServedEstimate, 1300000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTroopsServedEstimate Context triple: [Dennison Railroad Depot Museum, numberOfTroopsServedEstimate, 1300000]
-
A.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
B.
militaryUnitTypeServed
Indicates that an entity served in, or was a member of, a specific type of military unit.
-
C.
yearsOfMilitaryService
Indicates the number of years an entity has served or is recorded as serving in the military.
-
D.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
E.
numberOfBattalions
Indicates the quantitative relationship specifying how many battalions are associated with a given entity or context.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a04675e08190837a3717242fd0f9 |
completed | April 10, 2026, 7:01 a.m. |
| PD | Predicate disambiguation | batch_69d85dd6503c819081f9045e9d5c4f3f |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.