Triple
T31046582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chongsheng Temple |
E791141
|
entity |
| Predicate | mainPagodaHeight |
P178829
|
FINISHED |
| Object | about 69 meters |
—
|
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: about 69 meters | Statement: [Chongsheng Temple, mainPagodaHeight, about 69 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainPagodaHeight Context triple: [Chongsheng Temple, mainPagodaHeight, about 69 meters]
-
A.
eastPagodaHeight
Indicates that the relationship concerns the height measurement or height-related attribute of the east pagoda.
-
B.
centralStupaHeight
Indicates the height measurement of the central stupa in a given structure or site.
-
C.
hasPagoda
Indicates that one entity possesses, contains, or is characterized by the presence of a pagoda.
-
D.
hasFiveStoryPagoda
Indicates that an entity possesses or includes a pagoda structure specifically consisting of five stories.
-
E.
numberOfPagodasInPagodaForest
Indicates the numerical count of pagodas that are present within a given pagoda forest.
- 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_69f224ca2fa881908a3ac5fedf207b90 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71421e8d08190807ccfb15d0f0ddb |
completed | May 3, 2026, 9:23 a.m. |
Created at: April 29, 2026, 8:59 p.m.