Triple
T36943716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorna Fencer Napurrurla |
E913846
|
entity |
| Predicate | skinNameSystem |
P186761
|
FINISHED |
| Object | Warlpiri kinship system |
—
|
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: Warlpiri kinship system | Statement: [Lorna Fencer Napurrurla, skinNameSystem, Warlpiri kinship system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinNameSystem Context triple: [Lorna Fencer Napurrurla, skinNameSystem, Warlpiri kinship system]
-
A.
hasSkin
Indicates that one entity possesses skin as a covering or outer tissue layer.
-
B.
skinningMethod
Indicates the technique or process used to remove or separate the outer layer (such as skin or covering) from an object or material.
-
C.
surfaceColorNickname
Indicates that an entity has a commonly used or informal nickname referring specifically to its surface color.
-
D.
fruitSkinColor
Indicates the color of the outer skin or peel of a fruit.
-
E.
hasFacialSkinColor
Indicates that one entity has a specific facial skin color characterized or attributed by another entity.
- 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_69f76e8a6a5c81909c1febf32bf3fe23 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fa0a799b9081909bfa8293a22c4b00 |
completed | May 5, 2026, 3:19 p.m. |
Created at: May 3, 2026, 4:13 p.m.