Triple
T7819118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christine |
E181083
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Chris |
E282595
|
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: Chris | Statement: [Christine, hasDiminutive, Chris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Context triple: [Christine, hasDiminutive, Chris]
-
A.
Chris
chosen
Chris is a common shortened given name, typically used as a familiar or informal form of the name Christian.
-
B.
Chris
Chris is the socially awkward, overweight teenage son in the animated television series "Family Guy."
-
C.
Chris
Chris is a character appearing in the work "The Valkyries."
-
D.
Jay
Jay is a masculine given name commonly used in English-speaking countries, often derived from the jaybird or as a short form of names like Jason or James.
-
E.
Jay
Jay is a foul-mouthed, slacker stoner character from Kevin Smith’s View Askewniverse, best known as one half of the comedic duo Jay and Silent Bob.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf97247c481908b18287eb7ee0a53 |
completed | March 30, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb149266e88190a582b11d68702a6a |
completed | March 31, 2026, 12:25 a.m. |
Created at: March 30, 2026, 4:40 p.m.