Triple
T3275054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple of Olympian Zeus |
E68737
|
entity |
| Predicate | oneMoreColumnLies |
P47046
|
FINISHED |
| Object | on the ground |
—
|
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: on the ground | Statement: [Temple of Olympian Zeus, oneMoreColumnLies, on the ground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oneMoreColumnLies Context triple: [Temple of Olympian Zeus, oneMoreColumnLies, on the ground]
-
A.
numberOfColumnsOnFlanks
Indicates the count of columns located on the flanking sides of a structure or object.
-
B.
liesBelow
Indicates that one entity is positioned at a lower vertical level than another entity.
-
C.
numberOfLaterals
Indicates the count of lateral branches or side elements associated with a given entity or structure.
-
D.
overlies
Indicates that one entity is positioned directly above and covering or resting on another entity, often with partial or complete contact.
-
E.
liesIn
Indicates that one entity is located within the spatial, geographical, or conceptual boundaries of 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adaff8a440819092509bc8511b2785 |
completed | March 8, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69ada420167c81909b6e2702db296d9e |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada525bb2c8190b773efe6d696b6ab |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:10 p.m.