Triple
T36690498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Or Akiva cemetery |
E905941
|
entity |
| Predicate | placeNameInLanguage |
P24399
|
FINISHED |
| Object | בית העלמין אור עקיבא |
—
|
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: בית העלמין אור עקיבא | Statement: [Or Akiva cemetery, placeNameInLanguage, בית העלמין אור עקיבא]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placeNameInLanguage Context triple: [Or Akiva cemetery, placeNameInLanguage, בית העלמין אור עקיבא]
-
A.
hasLanguageOfToponym
chosen
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
B.
hasPlaceNamesakeIn
Indicates that something is named after a particular place or location.
-
C.
hasPlaceNamesIn
Indicates that something contains, references, or is associated with one or more place names within it.
-
D.
modernCityNameLanguage
Indicates that the modern name of a city is expressed in a particular language.
-
E.
countryNameLocal
Indicates the name of a country as expressed in its own local or official 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_69f76e70d2448190bdd3ce781ba971c5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fdb31800508190beec15adb9bbd292 |
completed | May 8, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69fdb19c381c8190bafb2f565da097f1 |
completed | May 8, 2026, 9:49 a.m. |
Created at: May 3, 2026, 4:12 p.m.