Triple
T19784858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahimaaz |
E475233
|
entity |
| Predicate | associatedWithLocation |
P2830
|
FINISHED |
| Object | En Rogel |
—
|
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: En Rogel | Statement: [Ahimaaz, associatedWithLocation, En Rogel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: En Rogel Context triple: [Ahimaaz, associatedWithLocation, En Rogel]
-
A.
Rog
Rog is a 2005 Indian Hindi-language thriller film directed by Himanshu Brahmbhatt, featuring Irrfan Khan in a prominent role.
-
B.
Rogasen
Rogasen is a locality historically associated with the birthplace of the renowned Talmudic scholar and lexicographer Marcus Jastrow.
-
C.
En-rogel
chosen
En-rogel is an ancient spring located just outside Jerusalem, mentioned in the Hebrew Bible as a notable landmark and gathering place.
-
D.
Roluos
Roluos is an archaeological site in Cambodia known for its group of early Angkorian temples that once formed the capital of the Khmer Empire.
-
E.
Ragalna
Ragalna is a small Italian town on the slopes of Mount Etna in Sicily, known for its volcanic landscapes and agricultural traditions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6538715b8819080c6930e7d16ab58 |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:49 p.m.