Triple
T11035735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hana |
E260879
|
entity |
| Predicate | hasRomanticPartner |
P9994
|
FINISHED |
| Object | Kip |
E48823
|
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: [Hana, hasRomanticPartner, Kip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kip Context triple: [Hana, hasRomanticPartner, Kip]
-
A.
Kip
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
chosen
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.
Kippa
Kippa is a young, fox-like Arcanic girl from the comic series "Monstress," known for her innocence, loyalty, and moral compass amid the story’s dark, war-torn world.
-
D.
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.
-
E.
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.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797e839e88190957c2eabf260c203 |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a9b70074819084c725c5babf2fb7 |
completed | April 18, 2026, 3:56 p.m. |
Created at: April 8, 2026, 9:25 p.m.