Triple
T1219296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Memorial Amphitheater |
E26180
|
entity |
| Predicate | hasColonnadeType |
P18962
|
FINISHED |
| Object | open-air marble colonnade |
—
|
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: open-air marble colonnade | Statement: [Memorial Amphitheater, hasColonnadeType, open-air marble colonnade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColonnadeType Context triple: [Memorial Amphitheater, hasColonnadeType, open-air marble colonnade]
-
A.
hasColonnade
chosen
Indicates that one entity features or is characterized by a colonnade in relation to another entity.
-
B.
hasMainHallType
Indicates the specific category or kind of main hall associated with an entity.
-
C.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
D.
hasBalustrades
Indicates that one entity features or is equipped with balustrades as part of its structure or design.
-
E.
hasCourtyard
Indicates that one entity includes, features, or is characterized by the presence of a courtyard.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be1d55a08190a138b2411a7c4376 |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.