Triple
T4782466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thai Ramakien |
E106397
|
entity |
| Predicate | notableDepictionLocation |
P15715
|
FINISHED |
| Object | Wat Phra Kaew murals |
—
|
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: Wat Phra Kaew murals | Statement: [Thai Ramakien, notableDepictionLocation, Wat Phra Kaew murals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableDepictionLocation Context triple: [Thai Ramakien, notableDepictionLocation, Wat Phra Kaew murals]
-
A.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
B.
notableDepictionBy
Indicates that an entity is significantly portrayed or represented by a particular creator, work, or medium.
-
C.
notableFilmingLocation
Indicates that a place served as a significant or well-known location where a film or television production was shot.
-
D.
notableLocationDocumented
Indicates that a specific location associated with an entity is recorded or documented as notable in some source or reference.
-
E.
notableLocationFeatured
chosen
Indicates that a particular location is prominently highlighted or showcased in relation to the subject.
- 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd69237f80819090713ed62653fb75 |
completed | March 20, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69bd622be1388190ab5511b589c878c0 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:22 p.m.