Triple
T35573087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple C |
E1027995
|
entity |
| Predicate | hasTriglyphs |
P200905
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Temple C, hasTriglyphs, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTriglyphs Context triple: [Temple C, hasTriglyphs, yes]
-
A.
hasGlyphsFor
Indicates that one entity provides or contains the necessary glyphs or visual symbols to represent another entity.
-
B.
hasGeometricPattern
Indicates that one entity exhibits or contains a repeated geometric design or arrangement in relation to another entity.
-
C.
hasStripePattern
Indicates that one entity exhibits a stripe-like visual pattern on its surface or body.
-
D.
hasLigatures
Indicates that one writing system, font, or text includes combined character forms (ligatures) that join two or more individual glyphs into a single symbol.
-
E.
hasTypography
Indicates that one entity uses, is associated with, or is characterized by a particular typographic style, font, or text layout.
- 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_69f76e0386688190b931bacdc145938c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffb82be8148190a1c870d467a28c80 |
completed | May 9, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69ffb7bbd550819094052e9a0d0ae320 |
completed | May 9, 2026, 10:39 p.m. |
| PDg | Predicate description generation | batch_69ffb82b40788190bf401344a3f288dd |
completed | May 9, 2026, 10:41 p.m. |
Created at: May 3, 2026, 4:04 p.m.