Triple
T24636893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | orca |
E609835
|
entity |
| Predicate | averageLengthFemale |
P38802
|
FINISHED |
| Object | 5 to 7 meters |
—
|
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: 5 to 7 meters | Statement: [orca, averageLengthFemale, 5 to 7 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageLengthFemale Context triple: [orca, averageLengthFemale, 5 to 7 meters]
-
A.
averageBodyLengthFemale
chosen
Indicates the typical or mean body length measured specifically for female individuals of a given group or species.
-
B.
averageFemaleHeight
Indicates the typical or mean height value observed among female individuals in a given group or population.
-
C.
averageBodyLengthM
Indicates the average length of an organism’s body, measured in meters.
-
D.
averageWingspanFemale
Indicates the typical or mean wingspan measurement specifically for female individuals of a given species or group.
-
E.
averageWeightFemale
Indicates the typical or mean body weight associated specifically with female individuals within a given group 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_69e2c4d28f848190ac38c400060e943d |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be064ff88190b5d9e5ec75a41242 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:33 a.m.