Triple
T29809931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch Palace |
E756929
|
entity |
| Predicate | hasSanctumDedicatedTo |
P178058
|
FINISHED |
| Object | Pazhayannur Bhagavathy |
—
|
NE NERFINISHED |
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: Pazhayannur Bhagavathy | Statement: [Dutch Palace, hasSanctumDedicatedTo, Pazhayannur Bhagavathy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSanctumDedicatedTo Context triple: [Dutch Palace, hasSanctumDedicatedTo, Pazhayannur Bhagavathy]
-
A.
hasMainSanctum
Indicates that an entity possesses a primary or central sacred space used for core religious or spiritual activities.
-
B.
hasSanctumCount
Indicates the number of sanctums associated with or contained by a given entity.
-
C.
hasSanctuary
Indicates that one entity provides or serves as a place of refuge, protection, or safe haven for another entity.
-
D.
hasSanctumImage
Indicates that an entity is associated with a specific image representing its sanctum or sacred/private space.
-
E.
hasOldSanctuary
Indicates that an entity possesses or is associated with an old or former sanctuary.
- 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_69f2245584848190ad4cab1f07752ccb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69f707f380388190954b79d52a321921 |
completed | May 3, 2026, 8:31 a.m. |
Created at: April 29, 2026, 5:23 p.m.