Triple
T18038439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saeed bin Suroor |
E431574
|
entity |
| Predicate | hasTrainedHorse |
P55479
|
FINISHED |
| Object | Daylami |
—
|
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: Daylami | Statement: [Saeed bin Suroor, hasTrainedHorse, Daylami]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daylami Context triple: [Saeed bin Suroor, hasTrainedHorse, Daylami]
-
A.
Daylami
chosen
Daylami was a champion Thoroughbred racehorse of the late 1990s, renowned for his versatility over middle and long distances and multiple Group/Grade 1 victories in Europe and North America.
-
B.
Mawlaik
Mawlaik is a town in northwestern Myanmar’s Sagaing Region, situated along the Chindwin River and serving as a local administrative and trading center.
-
C.
Samiyam
Samiyam is an American hip-hop producer and beatmaker known for his off-kilter, synth-heavy instrumentals and association with the Los Angeles beat scene.
-
D.
Hayssa
Hayssa is a town located within the Akkar Governorate in northern Lebanon.
-
E.
Muladis
Muladis were Muslims in medieval Iberia who were originally local Christians that had converted to Islam, often blending Arab-Islamic and Iberian cultural elements.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be3cbe8c8190ba216eeebfc3cbec |
completed | April 19, 2026, 11:36 a.m. |
Created at: April 10, 2026, 10:25 a.m.