Triple
T10396487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humans |
E245033
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Mia |
E429966
|
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: Mia | Statement: [Humans, hasCharacter, Mia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mia Context triple: [Humans, hasCharacter, Mia]
-
A.
Mia
chosen
Mia is a feminine given name used in many cultures, often as a short form of names like Maria or Amelia.
-
B.
Mia
Mia is a major fine art museum in Minneapolis, Minnesota, known for its extensive and diverse collection spanning thousands of years and cultures.
-
C.
Maddie
Maddie is the official mascot of the WNBA's New York Liberty basketball team.
-
D.
Maddie
Maddie is a common diminutive form of the given name Madeleine, often used as a casual or affectionate nickname.
-
E.
Zoe
"Zoe" is a 2018 science-fiction romantic drama film directed by Drake Doremus that explores love and relationships in a near-future world of advanced artificial intelligence and synthetic partners.
- 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_69d4e9cf79348190975d6c1791e3b621 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d795cf331c8190b35caf3997dc29a3 |
completed | April 9, 2026, 12:04 p.m. |
Created at: April 6, 2026, 12:06 p.m.