Triple
T16588196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple of Hercules (Amman) |
E403013
|
entity |
| Predicate | numberOfStandingColumns |
P106436
|
FINISHED |
| Object | several (commonly noted as six) large columns |
—
|
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: several (commonly noted as six) large columns | Statement: [Temple of Hercules (Amman), numberOfStandingColumns, several (commonly noted as six) large columns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStandingColumns Context triple: [Temple of Hercules (Amman), numberOfStandingColumns, several (commonly noted as six) large columns]
-
A.
hasNumberOfStandingColumns
chosen
Indicates the relationship specifying how many standing columns an entity currently has.
-
B.
currentStandingColumns
Indicates that certain columns are presently active, visible, or in use within a given context or layout.
-
C.
numberOfColumnsInColonnade
Indicates the count of individual columns that make up a given colonnade.
-
D.
numberOfColumnsOnFlanks
Indicates the count of columns located on the flanking sides of a structure or object.
-
E.
numberOfStandingPlaces
Indicates the total count of standing-only positions or spots available in a given context (e.g., a vehicle, venue, or area).
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3599e79288190b6bcdb6fe4a2d1fa |
completed | April 18, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69e296a7d9d0819088555bca6c936e79 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.