Triple
T16666051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperial Iranian Army |
E404983
|
entity |
| Predicate | sizePeakApproximate |
P6061
|
FINISHED |
| Object | 285000 personnel |
—
|
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: 285000 personnel | Statement: [Imperial Iranian Army, sizePeakApproximate, 285000 personnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sizePeakApproximate Context triple: [Imperial Iranian Army, sizePeakApproximate, 285000 personnel]
-
A.
approximateSize
chosen
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
-
B.
peakSize
Indicates the magnitude or height of a peak within a given signal, distribution, or dataset.
-
C.
approximateWeightInPounds
Indicates the estimated weight of an entity expressed in pounds, rather than an exact measured value.
-
D.
hasDimensionsApprox
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
-
E.
sizeDescription
Indicates a relationship where one entity provides descriptive information about the size or scale of another entity.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37c9cd7ec819084aa9b2830874bf5 |
completed | April 18, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.