Triple
T7661497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nilgiri tahr |
E173516
|
entity |
| Predicate | femaleWeightRange |
P26162
|
FINISHED |
| Object | around 50–60 kilograms |
—
|
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: around 50–60 kilograms | Statement: [Nilgiri tahr, femaleWeightRange, around 50–60 kilograms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleWeightRange Context triple: [Nilgiri tahr, femaleWeightRange, around 50–60 kilograms]
-
A.
averageWeightFemale
Indicates the typical or mean body weight associated specifically with female individuals within a given group or context.
-
B.
femaleHeightRangeCm
Indicates the range of heights, measured in centimeters, that is associated with female individuals.
-
C.
weightRangeDescription
chosen
Indicates the textual description that specifies the range within which an entity’s weight falls.
-
D.
averageWeight
Indicates the typical or mean weight value associated with an entity or group of entities.
-
E.
maleBodyMass
Indicates that the relationship specifies the body mass or weight associated with a male individual.
- 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_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7061cbc3c8190a917dd7e71214182 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015dd8fc8190bc5f52a12bd46209 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 3:59 p.m.