Triple
T13609978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ross Geller |
E325161
|
entity |
| Predicate | hasPet |
P8711
|
FINISHED |
| Object | Marcel |
E201405
|
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: Marcel | Statement: [Ross Geller, hasPet, Marcel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcel Context triple: [Ross Geller, hasPet, Marcel]
-
A.
Marcel
chosen
Marcel is a masculine given name of French origin, commonly used in various European countries.
-
B.
Marcel
Marcel is an American country music singer-songwriter who recorded for the Nashville-based label Lyric Street Records.
-
C.
Maurice
Maurice is a masculine given name of Latin origin, commonly used in English and French-speaking countries.
-
D.
Maurice
Maurice is a cautious, level-headed aye-aye who serves as King Julien’s loyal advisor and caretaker in the animated Penguins of Madagascar universe.
-
E.
Maurice
Maurice is the elderly, emotionally complex protagonist of the 2006 British film "Venus," portrayed by Peter O'Toole.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0aa9a1481908c6f92495aff86c6 |
completed | April 12, 2026, 2:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f98286c8190a866b5edc21f1225 |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:50 p.m.