Triple
T8122300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miranda Hart |
E189637
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Miranda |
E111839
|
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: Miranda | Statement: [Miranda Hart, givenName, Miranda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miranda Context triple: [Miranda Hart, givenName, Miranda]
-
A.
Miranda
chosen
Miranda is a common Spanish-origin surname shared by numerous notable individuals across the arts, politics, and other fields.
-
B.
Miranda
Miranda is one of Uranus's major moons, known for its unusually varied and geologically complex surface featuring dramatic cliffs and patchwork terrains.
-
C.
Miranda
Miranda is the compassionate and innocent daughter of Prospero in Shakespeare’s play "The Tempest," known for her wonder at the world beyond the island where she has been raised.
-
D.
Querença
Querença is a traditional rural village in Portugal’s Algarve region, known for its whitewashed houses, natural springs, and cultural festivals.
-
E.
Perla
Perla is a Mexican telenovela best known for starring actress Silvia Navarro in one of her early prominent roles.
- 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_69ca82bb74848190afb1f18640632c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb435cb30881909ccaa2f625e53799 |
completed | March 31, 2026, 3:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc945c743c8190bf1d8e60975bd8bc |
completed | April 1, 2026, 3:43 a.m. |
Created at: March 30, 2026, 5:33 p.m.