Triple
T31176723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple of Hera I |
E794768
|
entity |
| Predicate | hasEntasis |
P142040
|
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 of Hera I, hasEntasis, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEntasis Context triple: [Temple of Hera I, hasEntasis, yes]
-
A.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
B.
hasTwist
Indicates that an entity (such as a story, object, or feature) includes an unexpected change, reversal, or surprising element relative to what was previously established or anticipated.
-
C.
hasSerpentineAppearance
Indicates that an entity has a winding, snake-like or sinuous visual form or shape.
-
D.
hasBulge
chosen
Indicates that one entity possesses or exhibits a protruding or swollen part relative to its surrounding surface or structure.
-
E.
hasTensioningSystem
Indicates that an object is equipped with a mechanism specifically designed to apply, adjust, or maintain tension in another component 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_69f224d5b9708190b6ca79ad2fd3a28a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: April 29, 2026, 9:08 p.m.