Triple
T3559130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theresa |
E75291
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Tessa |
E213395
|
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: Tessa | Statement: [Theresa, hasDiminutive, Tessa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessa Context triple: [Theresa, hasDiminutive, Tessa]
-
A.
Tessa
chosen
Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
-
B.
Tamsin
Tamsin is a feminine given name of English origin, often associated with actresses and public figures such as Tamsin Egerton.
-
C.
Arielle
Arielle is a given name shared by various individuals, including Arielle Zuckerberg, a venture capitalist and younger sister of Meta co-founder Mark Zuckerberg.
-
D.
Talia
Talia is a feminine given name used in various cultures, often associated with meanings like “dew from heaven” or “to bloom.”
-
E.
Chloe
Chloe is the birth name of Nobel Prize–winning American novelist Toni Morrison, renowned for her powerful explorations of African American life and history.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0881d50819092332491b9527c9d |
completed | March 8, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3bb9983f48190bda2749d93c74a8d |
completed | March 13, 2026, 7:24 a.m. |
Created at: March 8, 2026, 3:20 p.m.