Triple
T2201855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School of Edessa |
E50506
|
entity |
| Predicate | notableAlumnus |
P304
|
FINISHED |
| Object | Narsai |
E46763
|
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: Narsai | Statement: [School of Edessa, notableAlumnus, Narsai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narsai Context triple: [School of Edessa, notableAlumnus, Narsai]
-
A.
Narsai
chosen
Narsai was a prominent 5th-century Syriac Christian theologian and poet, renowned for his extensive homilies and influential role in the Church of the East.
-
B.
Kynthia
Kynthia is an ancient Greek epithet and form of the name Cynthia, traditionally associated with the moon goddess Artemis and the island of Kynthos (Cynthus).
-
C.
Channah
Channah is a given name, often considered a variant of the Hebrew name Hannah, traditionally associated with grace or favor.
-
D.
Sharurah
Sharurah is a remote desert city in southern Saudi Arabia near the Yemeni border, known as a growing urban center within the Najran Region.
-
E.
Serein
Serein is a river in central France that flows through the Burgundy region before joining the Yonne River.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa1b41c8190b0f7467d0dcdfbcd |
completed | March 7, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6af5dc2081909d69641ca3bc65ea |
completed | March 9, 2026, 6:38 a.m. |
Created at: March 4, 2026, 7:46 p.m.