Triple
T12655321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ḥimṣ |
E302264
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Emesa |
E302263
|
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: Emesa | Statement: [Ḥimṣ, hasAlternativeName, Emesa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emesa Context triple: [Ḥimṣ, hasAlternativeName, Emesa]
-
A.
Emesa
chosen
Emesa is the ancient name of the Syrian city now known as Homs, historically significant as a religious and trading center in Roman and early Christian times.
-
B.
Eliada
Eliada is a lesser-known biblical figure mentioned in the Old Testament as one of King David’s sons.
-
C.
Almeirim
Almeirim is a Portuguese city in the Ribatejo region, known for its agricultural traditions and its famous sopa da pedra (stone soup).
-
D.
Huraymila
Huraymila is a small town in central Saudi Arabia known for its traditional character and location within the greater Riyadh region.
-
E.
Temara
Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961620b188190a8a8569f1133a9cf |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f668832c7081909eb75429efba493e |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:18 p.m.