Triple
T7088430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Hsieh |
E165132
|
entity |
| Predicate | boardMemberOf |
P10
|
FINISHED |
| Object | Zappos |
E31209
|
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: Zappos | Statement: [Tony Hsieh, boardMemberOf, Zappos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zappos Context triple: [Tony Hsieh, boardMemberOf, Zappos]
-
A.
Zappos
chosen
Zappos is a major U.S.-based online retailer best known for its extensive selection of shoes and its customer-centric service culture.
-
B.
Jet.com
Jet.com was an American e-commerce company known for its dynamic pricing model and rapid growth as a Walmart-acquired online retail platform.
-
C.
Karl's Shoe Stores
Karl's Shoe Stores was a prominent American retail shoe chain founded and owned by businessman Harry Karl.
-
D.
Nordstrom
Nordstrom is a leading American luxury department store chain known for its high-end fashion, quality customer service, and nationwide retail presence.
-
E.
Nordstrom Rack
Nordstrom Rack is an off-price retail chain owned by Nordstrom that sells discounted designer and brand-name apparel, shoes, and accessories.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e52d26f08190917e5e13b181bdae |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ad7f7cac81909c13fbb60acd9a69 |
completed | March 28, 2026, 10:29 a.m. |
Created at: March 27, 2026, 2:41 p.m.