Triple
T9355866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salt Lake 2002 mascots set |
E225135
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Timber
Timber is one of the official mascots of the Salt Lake City 2002 Winter Olympics, represented as an animal character symbolizing the spirit of the Games.
|
E793437
|
NE FINISHED |
How this triple was built (4 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: Timber | Statement: [Salt Lake 2002 mascots set, hasPart, Timber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timber Context triple: [Salt Lake 2002 mascots set, hasPart, Timber]
-
A.
How Wood
How Wood is a residential suburb and railway-served locality near St Albans in Hertfordshire, England.
-
B.
Mine Woods
Mine Woods is a woodland park and popular recreational area near Bridge of Allan in central Scotland, known for its walking trails, wildlife, and scenic views.
-
C.
Oaken
Oaken is a friendly shopkeeper and sauna owner from Disney's Frozen franchise, known for his cheerful demeanor and memorable "Yoo-hoo!" greeting.
-
D.
Woods
Woods is a common English surname of Anglo-Saxon origin, typically referring to someone who lived or worked in or near a forest.
-
E.
De Wood
De Wood is a specific variant or form of wood distinguished from the general category of wood materials.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Timber Triple: [Salt Lake 2002 mascots set, hasPart, Timber]
Generated description
Timber is one of the official mascots of the Salt Lake City 2002 Winter Olympics, represented as an animal character symbolizing the spirit of the Games.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Timber Target entity description: Timber is one of the official mascots of the Salt Lake City 2002 Winter Olympics, represented as an animal character symbolizing the spirit of the Games.
-
A.
How Wood
How Wood is a residential suburb and railway-served locality near St Albans in Hertfordshire, England.
-
B.
Mine Woods
Mine Woods is a woodland park and popular recreational area near Bridge of Allan in central Scotland, known for its walking trails, wildlife, and scenic views.
-
C.
Oaken
Oaken is a friendly shopkeeper and sauna owner from Disney's Frozen franchise, known for his cheerful demeanor and memorable "Yoo-hoo!" greeting.
-
D.
Woods
Woods is a common English surname of Anglo-Saxon origin, typically referring to someone who lived or worked in or near a forest.
-
E.
De Wood
De Wood is a specific variant or form of wood distinguished from the general category of wood materials.
- F. None of above. chosen
Provenance (5 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f99205c8190a5ad95926ef25497 |
completed | April 1, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e45b752c8190b7dd8981ba5be433 |
completed | April 4, 2026, 10:13 a.m. |
| NEDg | Description generation | batch_69d0e5760c0c8190b01a36772cea3058 |
completed | April 4, 2026, 10:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0e616d350819086465c7e491b6e62 |
completed | April 4, 2026, 10:21 a.m. |
Created at: March 30, 2026, 7:42 p.m.