Triple
T10389341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kip Thorne |
E244848
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Kip |
E248929
|
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: Kip | Statement: [Kip Thorne, hasGivenName, Kip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kip Context triple: [Kip Thorne, hasGivenName, Kip]
-
A.
Kip
chosen
Kip is the given name of Kip Thorne, the Nobel Prize–winning American theoretical physicist known for his work on gravitational physics and astrophysics.
-
B.
Kip
Kip is a young Sikh British-Indian army sapper in Michael Ondaatje’s novel "The English Patient," whose expertise in bomb disposal and complex relationship with the other characters explore themes of war, identity, and colonialism.
-
C.
Kin Kletso
Kin Kletso is an Ancestral Puebloan great house ruin in Chaco Canyon, New Mexico, notable for its masonry architecture and role in the Chacoan cultural landscape.
-
D.
Kai
Kai is a masculine given name used in various cultures, often associated with meanings such as "sea," "forgiveness," or "victory" depending on its linguistic origin.
-
E.
Kai
Kai is the supernatural yak warrior and primary antagonist in the animated film "Kung Fu Panda 3."
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9b40dd8819080ac839487020a44 |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fbae9a9c81908178fca68eb142b6 |
completed | April 9, 2026, 7:19 p.m. |
Created at: April 6, 2026, 12:05 p.m.