Triple
T17294151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apadana of Darius I |
E419860
|
entity |
| Predicate | columnCapitalType |
P126856
|
FINISHED |
| Object | double-headed animal capitals |
—
|
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: double-headed animal capitals | Statement: [Apadana of Darius I, columnCapitalType, double-headed animal capitals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: columnCapitalType Context triple: [Apadana of Darius I, columnCapitalType, double-headed animal capitals]
-
A.
columnType
Indicates the specific data type assigned to a column within a table or dataset.
-
B.
casingType
Indicates the specific kind or category of casing associated with or used by an entity.
-
C.
hasCapitalType
Indicates that a specified location’s capital is of a particular type (e.g., political, administrative, or economic capital).
-
D.
columnTitle
Indicates that one entity serves as the title or header label for a column associated with another entity.
-
E.
capitalizedOn
Indicates that one entity took advantage of, exploited, or made beneficial use of an opportunity, situation, or resource provided or created by 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e437869ec08190b4a63fb1ee6a71ee |
completed | April 19, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69e3b0118ad08190b119cd219c68ba67 |
completed | April 18, 2026, 4:23 p.m. |
| PDg | Predicate description generation | batch_69e3b2a225b08190a50f984caa6513b9 |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:40 a.m.