Triple
T7902679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samaritan (as-Samiri) |
E183492
|
entity |
| Predicate | distinguishedFrom |
P1612
|
FINISHED |
| Object | Harun (Aaron) |
E340775
|
NE 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: Harun (Aaron) | Statement: [Samaritan (as-Samiri), distinguishedFrom, Harun (Aaron)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harun (Aaron) Context triple: [Samaritan (as-Samiri), distinguishedFrom, Harun (Aaron)]
-
A.
Aharon
chosen
Aharon is a masculine given name of Hebrew origin, traditionally associated with the biblical figure Aaron and widely used in Jewish communities.
-
B.
Nadab
Nadab is a biblical figure, the eldest son of Aaron who served as a priest during the Israelites’ wilderness period.
-
C.
Nadab
Nadab was a king of the northern Kingdom of Israel in the Hebrew Bible, known as the son and short-reigning royal heir of Jeroboam I.
-
D.
Mūsa
Mūsa is a river in Latvia that serves as one of the main tributaries forming the larger Lielupe River.
-
E.
Abihu
Abihu is a biblical figure, one of the sons of Aaron who served as a priest and was killed for offering unauthorized fire before God.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a41b0fc81909890f2e4f432a5cf |
completed | March 31, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bc35cec8190bda3dfe7d8d4ed18 |
completed | March 31, 2026, 5:29 a.m. |
Created at: March 30, 2026, 5:02 p.m.