Triple
T17336855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tibbett |
E420958
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Tibbet |
—
|
NE ONNED1 |
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: Tibbet | Statement: [Tibbett, hasVariant, Tibbet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tibbet Context triple: [Tibbett, hasVariant, Tibbet]
-
A.
Tibbets
chosen
Tibbets is the surname of Paul W. Tibbets Jr., the American Air Force brigadier general who piloted the Enola Gay during the atomic bombing of Hiroshima in World War II.
-
B.
Wallichia
Wallichia is a genus of palms native to South and Southeast Asia, named in honor of the Danish botanist Nathaniel Wallich.
-
C.
Ü-Tsang
Ü-Tsang is the central historical region of Tibet, encompassing Lhasa and serving as the traditional political and cultural heartland of Tibetan civilization.
-
D.
Tajuan
Tajuan is the given first name of former NFL cornerback Ty Law.
-
E.
Zongtang
Zongtang is the given name of Zuo Zongtang, a prominent 19th-century Qing dynasty statesman and military leader known in the West as General Tso.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a12e1288190a81c30d6e1e9652f |
completed | April 19, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a019552a0208190bd8bd0f9588911c3 |
in_progress | May 11, 2026, 8:37 a.m. |
Created at: April 10, 2026, 5:43 a.m.