Triple
T20516211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Mallory |
E503688
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mallory |
—
|
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: Mallory | Statement: [George Mallory, familyName, Mallory]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mallory Context triple: [George Mallory, familyName, Mallory]
-
A.
Mallory
chosen
Mallory is an English surname most famously associated with mountaineer George Mallory, a key figure in early Everest expeditions.
-
B.
Maillane
Maillane is a small village in the Bouches-du-Rhône department of southern France, best known as the birthplace and home of Nobel Prize–winning Provençal poet Frédéric Mistral.
-
C.
Humphreys
Humphreys is a small unincorporated community located within Lea County in southeastern New Mexico.
-
D.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
E.
Hayes
Hayes is a town in the southern Jamaican parish of Clarendon, known historically for its sugar estates and bauxite-related industry.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f41eee481908121e54c7bd691ca |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.