Triple
T4791574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Howe Crane |
E106612
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Crane |
E100532
|
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: Crane | Statement: [William Howe Crane, familyName, Crane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crane Context triple: [William Howe Crane, familyName, Crane]
-
A.
Crane
chosen
Crane is a common English surname borne by numerous notable individuals across literature, politics, and other fields.
-
B.
Stork
The stork is a large, long-legged wading bird known for its migratory behavior and cultural associations with delivering babies in European folklore.
-
C.
Condor
Condor is a German leisure airline known for operating holiday flights to popular vacation destinations, primarily from bases in Germany.
-
D.
Argosy
Argosy is a British pulp magazine best known for publishing adventure and genre fiction during the early to mid-20th century.
-
E.
Wing
Wing is an experimental mobile operating system and user interface project developed by X (formerly Google X) to explore new paradigms in smartphone interaction and design.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65ddff388190b55071ed5cae7688 |
completed | March 20, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43ecf0308190941809fd13efa393 |
completed | March 21, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:22 p.m.