Triple
T4696161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Kemp |
E104146
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kemp |
E325923
|
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: Kemp | Statement: [Martin Kemp, familyName, Kemp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kemp Context triple: [Martin Kemp, familyName, Kemp]
-
A.
Kemp
chosen
Kemp is a surname most famously associated with former NBA All-Star forward Shawn Kemp, known for his high-flying dunks with the Seattle SuperSonics in the 1990s.
-
B.
Kempner
Kempner is a surname most notably associated with Karen Kempner Zuckerberg, the mother of Facebook co-founder Mark Zuckerberg.
-
C.
Kerian
Kerian is a given name used as a personal first name.
-
D.
Kashmore
Kashmore is a town in Pakistan’s Sindh province that serves as a regional hub near the Guddu Barrage on the Indus River.
-
E.
Kedzie
Kedzie is a Chicago Transit Authority rapid transit station on the Pink Line serving the city's West Side.
- 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd63b2eb708190962f460063615f9a |
completed | March 20, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03c3e6f48190b2f61de26192f5c4 |
completed | March 21, 2026, 2:34 a.m. |
Created at: March 20, 2026, 1:17 p.m.