Triple
T499542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Mara |
E10370
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mara |
E65229
|
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: Mara | Statement: [Kate Mara, familyName, Mara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mara Context triple: [Kate Mara, familyName, Mara]
-
A.
Mara
chosen
Mara is a surname of Irish origin borne by various notable individuals in fields such as sports, entertainment, and politics.
-
B.
Maia
Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
-
C.
Loralai
Loralai is a town and district in northern Balochistan, Pakistan, known historically as a regional administrative and trade center.
-
D.
Pauletta
Pauletta is a feminine given name, typically considered a diminutive or variant of Paula or Pauline.
-
E.
Zella
Zella is an activewear and athleisure clothing brand known for its performance-focused yet stylish designs, sold at Nordstrom.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f119b14c8190a5a6b119579c2682 |
completed | Feb. 28, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4b5d3b5f0819093c5d55bdf5a7c4d |
completed | March 1, 2026, 9:55 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.