Triple
T15715094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Hobbs |
E380940
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Hobbs |
E614753
|
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: Hobbs | Statement: [Michael Hobbs, hasFamilyName, Hobbs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hobbs Context triple: [Michael Hobbs, hasFamilyName, Hobbs]
-
A.
Hobbs
Hobbs is a city in southeastern New Mexico known for its oil and gas industry and proximity to the Texas border.
-
B.
Hobbs
chosen
Hobbs is a surname of English origin borne by various notable individuals across fields such as politics, sports, and the arts.
-
C.
Hobbs, New Mexico
Hobbs, New Mexico is a city in southeastern New Mexico known for its oil and gas industry and role as a regional economic and educational hub near the Texas border.
-
D.
Philmore
Philmore is a character appearing in the 1914 silent film "Jitney," likely serving as one of its supporting comedic roles.
-
E.
Huntertown
Huntertown is a small town in Allen County, Indiana, known as a growing residential community near Fort Wayne.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f90aea0819082a9e9fe0f7780b0 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff7581302c8190918266f04bcf2231 |
completed | May 9, 2026, 5:57 p.m. |
Created at: April 10, 2026, 4:45 a.m.