Triple
T1741757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dama dama |
E38247
|
entity |
| Predicate | averageWeightFemale |
P31786
|
FINISHED |
| Object | 30–50 kg |
—
|
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: 30–50 kg | Statement: [Dama dama, averageWeightFemale, 30–50 kg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageWeightFemale Context triple: [Dama dama, averageWeightFemale, 30–50 kg]
-
A.
averageWeight
Indicates the typical or mean weight value associated with an entity or group of entities.
-
B.
numberOfFemaleAthletes
Indicates the count of athletes who are female in a given context or group.
-
C.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
-
D.
weight
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
-
E.
weightRangeDescription
Indicates the textual description that specifies the range within which an entity’s weight falls.
- F. None of above. chosen
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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab3c2559ac8190905186406fcaccb9 |
completed | March 6, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69aa61c4023c819099cbe439aefda71f |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab3c2479148190badc616f8e2686d4 |
completed | March 6, 2026, 8:42 p.m. |
Created at: March 4, 2026, 7:30 p.m.