Triple
T4559977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allison Janney |
E120568
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Mom |
E120569
|
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: Mom | Statement: [Allison Janney, notableWork, Mom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mom Context triple: [Allison Janney, notableWork, Mom]
-
A.
Mom
chosen
Mom is a popular American sitcom starring Allison Janney and Anna Faris that follows a dysfunctional mother-daughter duo in recovery from addiction.
-
B.
MOM
MOM is India’s first interplanetary spacecraft, a Mars orbiter launched by ISRO that made India the first Asian nation to reach Martian orbit.
-
C.
Mam
Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
-
D.
Mamayi
Mamayi was a powerful 14th-century military and political leader of the Golden Horde who played a central role in its internal power struggles and conflicts with emerging Russian principalities.
-
E.
Mothers
Mothers is a section of the Tokyo Stock Exchange dedicated to emerging and high-growth startup companies seeking public investment.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd582b871c8190be0b70c76d639000 |
completed | March 20, 2026, 2:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdc593eaf881908a9043366230b391 |
completed | March 20, 2026, 10:09 p.m. |
Created at: March 20, 2026, 1:09 p.m.