Triple
T4663583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watch Over Me |
E102790
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Gabriella |
E307088
|
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: Gabriella | Statement: [Watch Over Me, hasCharacter, Gabriella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabriella Context triple: [Watch Over Me, hasCharacter, Gabriella]
-
A.
Gabriella
chosen
Gabriella is a feminine given name of Italian origin, commonly used in many languages and often associated with the meaning "God is my strength."
-
B.
Gabrielle
Gabrielle is the given name of Émilie du Châtelet, the renowned 18th-century French mathematician, physicist, and translator of Newton.
-
C.
Gabrielle
Gabrielle is a central character in the action film "Rambo: Last Blood," serving as John Rambo’s beloved niece whose kidnapping drives the movie’s main conflict.
-
D.
Gabrielle Starr
Gabrielle Starr is an American literary scholar and academic administrator who serves as the president of Pomona College.
-
E.
Gabriella Martinelli
Gabriella Martinelli is a Canadian film and television producer best known for her work on high-profile projects such as Baz Luhrmann’s "Romeo + Juliet."
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd632d6150819085bab97021c0235a |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03803a948190b6dc2a03bb9cdc93 |
completed | March 21, 2026, 2:33 a.m. |
Created at: March 20, 2026, 1:15 p.m.