Triple
T11682751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah McKean |
E277658
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | McKean |
E152696
|
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: McKean | Statement: [Sarah McKean, familyName, McKean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McKean Context triple: [Sarah McKean, familyName, McKean]
-
A.
McKean
chosen
McKean is a Scottish and Irish surname borne by various notable individuals, including American Founding Father Thomas McKean.
-
B.
Kallahan
Kallahan is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
-
C.
Paxton
Paxton is a small rural village in the Scottish Borders region of southeastern Scotland.
-
D.
Paxton
Paxton is a surname most prominently associated with the late American actor and filmmaker Bill Paxton, known for his roles in films like "Twister," "Aliens," and "Titanic."
-
E.
Paxton
Paxton is a central character in the horror film "Hostel," portrayed as an American tourist whose vacation in Europe turns into a brutal fight for survival.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a462bb2881909238107d34c0a28d |
completed | April 10, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef142269d08190a9e5cf8d6268168b |
completed | April 27, 2026, 7:45 a.m. |
Created at: April 8, 2026, 9:40 p.m.