Triple
T8625488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mother (1926 film) |
E204269
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Mat |
E354151
|
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: Mat | Statement: [Mother (1926 film), alsoKnownAs, Mat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mat Context triple: [Mother (1926 film), alsoKnownAs, Mat]
-
A.
Mat
chosen
Mat is a common shortened form of the given name Matthew, often used as an informal or familiar nickname.
-
B.
Mate
Mate is a Croatian entrepreneur and engineer best known as the founder and CEO of electric hypercar manufacturer Rimac Automobili.
-
C.
Ma
Ma is a fictional character appearing in Enid Blyton’s children’s adventure novel "The Circus of Adventure."
-
D.
Ma
Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
-
E.
Ma
Ma is a 2019 psychological horror film starring Octavia Spencer as a lonely woman who befriends a group of teenagers with increasingly disturbing consequences.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc472a07908190a2368975459543f9 |
completed | March 31, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebbf03c688190a989f16675f6e8a6 |
completed | April 2, 2026, 6:56 p.m. |
Created at: March 30, 2026, 6:26 p.m.