Triple
T10982561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rabbula of Edessa |
E259544
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Edessa |
E46023
|
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: Edessa | Statement: [Rabbula of Edessa, placeOfDeath, Edessa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edessa Context triple: [Rabbula of Edessa, placeOfDeath, Edessa]
-
A.
Edessa
chosen
Edessa was an ancient city in Upper Mesopotamia, renowned as a major early center of Syriac Christianity and culture.
-
B.
Edessa
Edessa is a historic city in northern Greece renowned for its picturesque waterfalls and ancient heritage.
-
C.
EDESSA
EDESSA is the company responsible for managing and operating Estadio Cuscatlán, one of the largest and most important football stadiums in El Salvador.
-
D.
Hierapolis
Hierapolis was an ancient Greco-Roman city in Phrygia (modern-day Turkey), known for its hot springs and as an early center of Christianity.
-
E.
Turkmenabat
Turkmenabat is one of the largest cities in Turkmenistan, serving as an important industrial, transport, and cultural center in the country’s east near the border with Uzbekistan.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d772eb518c8190a885a417815f2ff6 |
completed | April 9, 2026, 9:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344c77d6c8190a9b5e2cc967fb031 |
completed | April 18, 2026, 8:45 a.m. |
Created at: April 8, 2026, 9:24 p.m.