Triple
T4832220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joshua Schachter |
E107969
|
entity |
| Predicate | coFounded |
P104
|
FINISHED |
| Object | Tasty Labs |
E473161
|
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: Tasty Labs | Statement: [Joshua Schachter, coFounded, Tasty Labs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tasty Labs Context triple: [Joshua Schachter, coFounded, Tasty Labs]
-
A.
Tasty Labs
chosen
Tasty Labs was a startup company co-founded by del.icio.us creator Joshua Schachter that focused on building social and task-oriented web applications.
-
B.
Founders Lab
Founders Lab is an innovation and entrepreneurship space at Elmhurst University that supports student startups and experiential learning in business and technology.
-
C.
Hatch Labs
Hatch Labs is a mobile technology incubator and startup studio best known for creating the popular dating app Tinder.
-
D.
Pyra Labs
Pyra Labs is the software company best known for creating Blogger, one of the earliest and most influential web-based blogging platforms.
-
E.
Pym Tasting Lab
Pym Tasting Lab is a Marvel-themed eatery and bar in Disney’s Avengers Campus that playfully uses “Pym Particle” science to serve creatively sized snacks and beverages.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6cc924e08190b03a7541c629aff9 |
completed | March 20, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cb748d081908fc32b2cea994b35 |
completed | March 21, 2026, 8:54 a.m. |
Created at: March 20, 2026, 1:24 p.m.