Triple
T6428507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jabez Howland |
E128119
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Howland |
E354877
|
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: Howland | Statement: [Jabez Howland, familyName, Howland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howland Context triple: [Jabez Howland, familyName, Howland]
-
A.
Howland
chosen
Howland is an English-origin surname borne by various notable individuals in American history and public life.
-
B.
Linwood
Linwood is a residential neighborhood located within the city of Milwaukie, Oregon.
-
C.
Linwood
Linwood is a small Scottish town in Renfrewshire, near Paisley, known historically for its car manufacturing and as a residential commuter community for the Greater Glasgow area.
-
D.
Willart
Willart is a given name or surname that functions as a variant spelling of Willard.
-
E.
Hadleyville
Hadleyville is the fictional small Western town in the classic 1952 film "High Noon," where the story’s tense showdown unfolds.
- 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06922a27881908c5571f2aa31e0c1 |
completed | March 22, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640e678608190b5a1dcd1076bc1f2 |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:44 p.m.