Triple
T671572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gallifrey |
E12981
|
entity |
| Predicate | notableLeader |
P304
|
FINISHED |
| Object | Rassilon |
E84830
|
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: Rassilon | Statement: [Gallifrey, notableLeader, Rassilon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rassilon Context triple: [Gallifrey, notableLeader, Rassilon]
-
A.
Rassilon
chosen
Rassilon is a legendary Time Lord from the Doctor Who universe, renowned as one of the founders and first leaders of Time Lord society.
-
B.
Daniel Quasar
Daniel Quasar is a graphic designer best known for creating the Progress Pride Flag, an updated version of the rainbow flag that emphasizes inclusion and intersectionality within the LGBTQ+ community.
-
C.
Roland Caulder
Roland Caulder is an actor known for his role in the film "The Iron Mask."
-
D.
the War Doctor
The War Doctor is a previously unseen incarnation of the Doctor in the Doctor Who universe, portrayed by John Hurt as a battle-hardened Time Lord who fought in the Last Great Time War.
-
E.
Time Lord
A Time Lord is a fictional, time-traveling humanoid species from the planet Gallifrey in the Doctor Who universe, known for their ability to regenerate and their mastery of time and space.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a021b908819086f7cfe65def4728 |
completed | March 1, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a6374a189c81908f7bc0828e9ff382 |
completed | March 3, 2026, 1:20 a.m. |
Created at: March 1, 2026, 7:36 p.m.