Triple
T16892102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tibbits |
E424198
|
entity |
| Predicate | likelyDerivedFrom |
P909
|
FINISHED |
| Object | Tibb |
E420965
|
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: Tibb | Statement: [Tibbits, likelyDerivedFrom, Tibb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tibb Context triple: [Tibbits, likelyDerivedFrom, Tibb]
-
A.
Tibb
chosen
Tibb is a medieval English given name, often a diminutive of names like Theobald or Tibalt, that later appeared as a root for surnames such as Tibbets.
-
B.
Tawthalin
Tawthalin is a traditional month in the Burmese calendar, associated with late monsoon season and various cultural and religious observances in Myanmar.
-
C.
Tibás
Tibás is an urban canton in Costa Rica known for being part of the Greater San José metropolitan area and home to the popular football club Deportivo Saprissa.
-
D.
Tibarg
Tibarg is the central shopping and main thoroughfare of the Hamburg district Niendorf, known for its retail stores and local amenities.
-
E.
Torbeshi
Torbeshi are a Slavic-speaking Muslim ethnic group primarily living in North Macedonia and neighboring Balkan regions.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc5a5308190937ebd05356bd91d |
completed | April 18, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2c414b081909b98e40ee9a176e2 |
completed | May 10, 2026, 5:39 p.m. |
Created at: April 10, 2026, 5:29 a.m.