Triple
T319212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hessian troops |
E7774
|
entity |
| Predicate | approximateStrength |
P2981
|
FINISHED |
| Object | 30000 |
—
|
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: 30000 | Statement: [Hessian troops, approximateStrength, 30000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateStrength Context triple: [Hessian troops, approximateStrength, 30000]
-
A.
estimatedStrength
chosen
Indicates that a value represents an approximate or inferred level, magnitude, or intensity of something rather than a precisely measured strength.
-
B.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
C.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
D.
approximateMass
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another entity.
-
E.
strength
Indicates the degree of power, intensity, or effectiveness with which an entity can act on, influence, or withstand another entity or force.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7df63c8190b7cd1bcfdfd96187 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e94513ec819089f5177f7a521e65 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.