Triple
T3869999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watson |
E91959
|
entity |
| Predicate | derivedFromGivenName |
P17
|
FINISHED |
| Object |
Wat
Wat is a medieval English diminutive form of the given name Walter, historically used as a familiar or nickname.
|
E396298
|
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: Wat | Statement: [Watson, derivedFromGivenName, Wat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wat Context triple: [Watson, derivedFromGivenName, Wat]
-
A.
WAT
WAT is the National Rail station code for London Waterloo, one of the busiest and most important railway terminals in the United Kingdom.
-
B.
Walo
Walo was a precolonial West African kingdom in the lower Senegal River region, known as one of the successor states to the Wolof Empire.
-
C.
Ne Win
Ne Win was a Burmese military leader and politician who ruled Myanmar for decades after seizing power in a 1962 coup, establishing an authoritarian socialist regime.
-
D.
W.
W. is a 2008 biographical drama film directed by Oliver Stone that portrays the life and presidency of George W. Bush.
-
E.
Wald
Wald is a surname most notably associated with Abraham Wald, a pioneering statistician known for his work on statistical decision theory and survivorship bias during World War II.
- 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: Wat Triple: [Watson, derivedFromGivenName, Wat]
Generated description
Wat is a medieval English diminutive form of the given name Walter, historically used as a familiar or nickname.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wat Target entity description: Wat is a medieval English diminutive form of the given name Walter, historically used as a familiar or nickname.
-
A.
WAT
WAT is the National Rail station code for London Waterloo, one of the busiest and most important railway terminals in the United Kingdom.
-
B.
Walo
Walo was a precolonial West African kingdom in the lower Senegal River region, known as one of the successor states to the Wolof Empire.
-
C.
Ne Win
Ne Win was a Burmese military leader and politician who ruled Myanmar for decades after seizing power in a 1962 coup, establishing an authoritarian socialist regime.
-
D.
W.
W. is a 2008 biographical drama film directed by Oliver Stone that portrays the life and presidency of George W. Bush.
-
E.
Wald
Wald is a surname most notably associated with Abraham Wald, a pioneering statistician known for his work on statistical decision theory and survivorship bias during World War II.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec533828819080f52dae15fdbecd |
completed | March 9, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5124769c081909111b4bcac6baa78 |
completed | March 14, 2026, 7:46 a.m. |
| NEDg | Description generation | batch_69b5161242f881908e62d0b7cf8e44b9 |
completed | March 14, 2026, 8:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5167379cc819088b4d20558622948 |
completed | March 14, 2026, 8:04 a.m. |
Created at: March 9, 2026, 3:20 p.m.