Triple
T25809596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady of Brassempouy |
E650069
|
entity |
| Predicate | headgearDepiction |
P128303
|
FINISHED |
| Object | checkerboard-patterned hair or headdress |
—
|
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: checkerboard-patterned hair or headdress | Statement: [Lady of Brassempouy, headgearDepiction, checkerboard-patterned hair or headdress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: headgearDepiction Context triple: [Lady of Brassempouy, headgearDepiction, checkerboard-patterned hair or headdress]
-
A.
headCovering
Indicates that one entity serves as a covering or protection for the head of another entity.
-
B.
headAttachment
Indicates that one entity is physically or structurally attached to the head or top part of another entity.
-
C.
oftenDepictedWearing
chosen
Indicates that an entity is frequently shown or represented as wearing a particular item or type of clothing in depictions or portrayals.
-
D.
hasHeadbandType
Indicates that an entity is associated with a specific type or style of headband.
-
E.
headType
Indicates the specific kind or category of head associated with an entity (e.g., type of head part, head role, or head classification in a structure or system).
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f600c37d40819086cc056057c25629 |
completed | May 2, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69f4a0fed15881909b789251fe5d8d45 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 22, 2026, 7:08 a.m.