Triple
T11042185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenham Stakes |
E261043
|
entity |
| Predicate | notableWinner |
P2766
|
FINISHED |
| Object |
Muhaarar
Muhaarar is a British Thoroughbred racehorse best known as a top-class sprinter and European champion three-year-old sprinter in 2015.
|
E900942
|
NE FINISHED |
How this triple was built (4 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: Muhaarar | Statement: [Greenham Stakes, notableWinner, Muhaarar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muhaarar Context triple: [Greenham Stakes, notableWinner, Muhaarar]
-
A.
Kallar Kahar
Kallar Kahar is a town in Pakistan’s Punjab province known for its scenic lake, historic Mughal-era garden, and location along the M2 Motorway.
-
B.
Omaar
Omaar is an alternative spelling of the given name Omar, commonly used in various cultures.
-
C.
Tareeno
Tareeno is an alternative name for Wanetsi, an Eastern Iranian language closely related to Pashto and spoken primarily in parts of Pakistan and Afghanistan.
-
D.
Humera
Humera is a town in northwestern Ethiopia near the borders with Eritrea and Sudan, known for its strategic location and sesame production.
-
E.
Miranshah
Miranshah is the main administrative and commercial town of North Waziristan in Pakistan’s Khyber Pakhtunkhwa province, near the border with Afghanistan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Muhaarar Triple: [Greenham Stakes, notableWinner, Muhaarar]
Generated description
Muhaarar is a British Thoroughbred racehorse best known as a top-class sprinter and European champion three-year-old sprinter in 2015.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Muhaarar Target entity description: Muhaarar is a British Thoroughbred racehorse best known as a top-class sprinter and European champion three-year-old sprinter in 2015.
-
A.
Kallar Kahar
Kallar Kahar is a town in Pakistan’s Punjab province known for its scenic lake, historic Mughal-era garden, and location along the M2 Motorway.
-
B.
Omaar
Omaar is an alternative spelling of the given name Omar, commonly used in various cultures.
-
C.
Tareeno
Tareeno is an alternative name for Wanetsi, an Eastern Iranian language closely related to Pashto and spoken primarily in parts of Pakistan and Afghanistan.
-
D.
Humera
Humera is a town in northwestern Ethiopia near the borders with Eritrea and Sudan, known for its strategic location and sesame production.
-
E.
Miranshah
Miranshah is the main administrative and commercial town of North Waziristan in Pakistan’s Khyber Pakhtunkhwa province, near the border with Afghanistan.
- F. None of above. chosen
Provenance (5 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7980134c8819098122d83380a1f79 |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a9e525508190bf3a728683eeec79 |
completed | April 18, 2026, 3:57 p.m. |
| NEDg | Description generation | batch_69e3ad024ee88190948d5d1c327fd063 |
completed | April 18, 2026, 4:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3b1fff754819092d634f46fb42387 |
completed | April 18, 2026, 4:32 p.m. |
Created at: April 8, 2026, 9:26 p.m.