Triple
T1027145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple of Hera at Olympia |
E22163
|
entity |
| Predicate | hasPlanType |
P8653
|
FINISHED |
| Object | rectangular ground plan |
—
|
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: rectangular ground plan | Statement: [Temple of Hera at Olympia, hasPlanType, rectangular ground plan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlanType Context triple: [Temple of Hera at Olympia, hasPlanType, rectangular ground plan]
-
A.
hasPlan
Indicates that an entity possesses or is associated with a specific plan or course of action.
-
B.
offersPlanType
Indicates that one entity provides or makes available a specific type of plan to another entity or in a given context.
-
C.
planType
chosen
Indicates the specific category or kind of plan associated with an entity, such as its level, structure, or intended use.
-
D.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
E.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95d35888190a20593a278175df7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7276180819085c6b23501a6a6e0 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.