Triple
T24473622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pays Bigouden |
E617168
|
entity |
| Predicate | hasTraditionalHeaddressHeight |
P156238
|
FINISHED |
| Object | very tall |
—
|
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: very tall | Statement: [Pays Bigouden, hasTraditionalHeaddressHeight, very tall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalHeaddressHeight Context triple: [Pays Bigouden, hasTraditionalHeaddressHeight, very tall]
-
A.
traditionalHeaddress
Indicates that an entity wears or is associated with a culturally traditional headdress as part of customary or ceremonial attire.
-
B.
headdressType
Indicates the specific kind or category of headdress associated with an entity.
-
C.
hasTraditionalAttire
Indicates that an entity possesses or is associated with clothing that is customary or traditional within a particular culture or community.
-
D.
estimatedHeadHeightInMeters
Indicates the estimated vertical height of a person's head, measured in meters.
-
E.
obverseHeaddressType
Indicates the type or style of headdress depicted on the obverse (front) side of an object, typically a coin or medal.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f299457ce081909e8d95fd482928dc |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:20 a.m.