Triple
T18662279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fflewddur Fflam |
E456230
|
entity |
| Predicate | hasCompanion |
P22642
|
FINISHED |
| Object | Gurgi |
—
|
NE NERFINISHED |
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: Gurgi | Statement: [Fflewddur Fflam, hasCompanion, Gurgi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gurgi Context triple: [Fflewddur Fflam, hasCompanion, Gurgi]
-
A.
Gurgi
chosen
Gurgi is a timid yet loyal, creature-like companion character from Disney’s animated fantasy film "The Black Cauldron."
-
B.
Fufluns
Fufluns is an Etruscan god associated with wine, vegetation, and rebirth, roughly analogous to the Greek Dionysus.
-
C.
Nagg
Nagg is a legless, elderly character in Samuel Beckett’s play "Endgame," known for living in a trash bin and engaging in bleakly comic exchanges with his wife Nell.
-
D.
Bugrino
Bugrino is a small remote settlement that serves as the main inhabited community on Kolguev Island in the Barents Sea, within Russia’s Nenets Autonomous Okrug.
-
E.
Iznogoud
Iznogoud is a French comic book series featuring a scheming grand vizier whose obsessive goal is to overthrow the caliph and become ruler in his place.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5508b35ec819085c1c4c2c98d6672 |
completed | April 19, 2026, 10 p.m. |
Created at: April 10, 2026, 11:48 a.m.