Triple
T11170969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melissa |
E264271
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Missy |
E90859
|
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: Missy | Statement: [Melissa, hasDiminutive, Missy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Missy Context triple: [Melissa, hasDiminutive, Missy]
-
A.
Missy
chosen
Missy is the female incarnation of the Master, a recurring Time Lord villain and nemesis of the Doctor in the British science fiction series Doctor Who.
-
B.
Misti
Misti is a prominent, snow-capped stratovolcano overlooking the city of Arequipa in southern Peru.
-
C.
Kizzy
Kizzy is a memorable character from Alex Haley’s saga "Roots," portrayed as a strong, resilient woman who embodies the struggles and spirit of enslaved African Americans.
-
D.
Minx
Minx is an American comedy-drama television series set in the 1970s publishing world that follows the creation of a pioneering feminist erotic magazine.
-
E.
Yessie
Yessie is a studio album by Canadian singer-songwriter Jessie Reyez that showcases her emotionally raw R&B and pop sound.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e89660208190b1d9e91529f5d246 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e463b155a08190b361b38a39d25b1f |
completed | April 19, 2026, 5:10 a.m. |
Created at: April 8, 2026, 9:29 p.m.