Triple
T16138437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica |
E391589
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Jess |
E940936
|
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: Jess | Statement: [Jessica, hasDiminutive, Jess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jess Context triple: [Jessica, hasDiminutive, Jess]
-
A.
Jess
Jess is a supporting character in the romantic comedy film "When Harry Met Sally..." who serves as Harry’s best friend and provides comic relief and relationship advice.
-
B.
Jess
chosen
Jess is the affectionate nickname commonly used for the character Jessica Day.
-
C.
Jennifer
Jennifer is a common feminine given name of English origin, derived from the Cornish form of Guinevere and widely used in many English-speaking countries.
-
D.
Jennifer
"Jennifer" is the viral R&B-pop single by American singer Trinidad Cardona that gained widespread attention online and launched his music career.
-
E.
Jane
Jane is a feminine given name of English origin that has been widely used in many English-speaking countries for centuries.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a06e0988190b5cd62d422d058a2 |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2b574148190b9d5b725d7d113af |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 5:01 a.m.