Triple
T31534892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hi Jolly Cemetery |
E804577
|
entity |
| Predicate | hasPlaqueTextLanguage |
P67509
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Hi Jolly Cemetery, hasPlaqueTextLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlaqueTextLanguage Context triple: [Hi Jolly Cemetery, hasPlaqueTextLanguage, English]
-
A.
hasPlaqueText
Indicates that an entity bears or is associated with a specific textual inscription, such as the wording on a plaque or sign.
-
B.
hasLanguageOnPlaque
chosen
Indicates that a specific language appears in the text or inscription displayed on a particular plaque.
-
C.
hasPlaqueTextTopic
Indicates that the topic specified is the subject or main theme of the text written on a plaque.
-
D.
hasPlaquePlacement
Indicates that a plaque has been positioned or installed at a specific location or on a particular object.
-
E.
hasLanguageRepresentation
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
Created at: April 30, 2026, 10:03 p.m.