Triple
T3064786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurene Powell |
E62077
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Laurene |
E64926
|
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: Laurene | Statement: [Laurene Powell, givenName, Laurene]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laurene Context triple: [Laurene Powell, givenName, Laurene]
-
A.
Laurene
chosen
Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
-
B.
Lauren
Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
-
C.
Laura
Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
-
D.
Laura
Laura is a feminine given name of Latin origin, commonly used in many languages and cultures.
-
E.
Bridgette
Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9ea2154c8190ab243feb77170a15 |
completed | March 8, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1ef1402108190a2d24e7eb523f658 |
completed | March 11, 2026, 10:39 p.m. |
Created at: March 8, 2026, 3:02 p.m.