Triple
T36800783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manila Chinese Cemetery |
E909315
|
entity |
| Predicate | languageUsedOnGravestones |
P142245
|
FINISHED |
| Object | Chinese |
—
|
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: Chinese | Statement: [Manila Chinese Cemetery, languageUsedOnGravestones, Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedOnGravestones Context triple: [Manila Chinese Cemetery, languageUsedOnGravestones, Chinese]
-
A.
hasGravestonesWithLanguage
chosen
Indicates that a burial site contains gravestones inscribed in a specified language.
-
B.
hasGraveInscription
Indicates that an entity (typically a grave or tomb) bears a specific inscription engraved or written on it.
-
C.
numberOfHeadstones
Indicates the total count of headstones associated with a given entity or location.
-
D.
hasLanguageOnPlaque
Indicates that a specific language appears in the text or inscription displayed on a particular plaque.
-
E.
memorialInscription
Indicates that a text is inscribed on a memorial object to commemorate a person, event, or occasion.
- 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_69f76e7b98888190899b6478a82ad6ae |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a014a0b57dc8190b04ce51156ab95fa |
completed | May 11, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_6a0149afa57c8190a83257085766d916 |
completed | May 11, 2026, 3:14 a.m. |
Created at: May 3, 2026, 4:12 p.m.