Triple
T8603788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Blount |
E203745
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Blount |
E390421
|
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: Blount | Statement: [Elizabeth Blount, familyName, Blount]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blount Context triple: [Elizabeth Blount, familyName, Blount]
-
A.
Blount
chosen
Blount is the surname of James Hillier Blount, better known as the English singer-songwriter James Blunt.
-
B.
Bowlegs
Bowlegs was a prominent Seminole leader and war chief known for resisting U.S. expansion during the early 19th-century Seminole conflicts in Florida.
-
C.
Osgood
Osgood is a surname of English origin borne by various notable individuals, including publishers, politicians, and athletes.
-
D.
Sprengelkiez
Sprengelkiez is a residential neighborhood in Berlin’s Wedding district known for its canalside location, historic buildings, and vibrant local community.
-
E.
Schlatter
Schlatter is a German-language surname borne by various notable individuals across fields such as entertainment, sports, and academia.
- 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46dc23448190a5eb63455578427e |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea8f8dfa4819080c8ed475a84be41 |
completed | April 2, 2026, 5:35 p.m. |
Created at: March 30, 2026, 6:24 p.m.