Triple
T23900299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lion |
E601022
|
entity |
| Predicate | bodyLengthWithoutTail |
P154004
|
FINISHED |
| Object | 1.4–2.5 m |
—
|
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: 1.4–2.5 m | Statement: [Lion, bodyLengthWithoutTail, 1.4–2.5 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodyLengthWithoutTail Context triple: [Lion, bodyLengthWithoutTail, 1.4–2.5 m]
-
A.
tailLengthObserved
Indicates that an observation has been made recording the length of an entity’s tail.
-
B.
hasTailLengthRange
Indicates that an entity is associated with a specified minimum and maximum length for its tail.
-
C.
tailLengthMale
Indicates the length of the tail specifically for male individuals in the context of the described relationship or measurement.
-
D.
bodyNumber
Indicates the numerical position or identifier assigned to a body within a sequence or collection of bodies.
-
E.
snoutVentLength
Indicates the measured distance from the tip of an animal’s snout to the opening of its vent (cloaca), typically used as a standard body length metric.
- 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cdddca088190b6c26df984a143ad |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 8:26 p.m.