Triple
T1261329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Håkon Wium Lie |
E12506
|
entity |
| Predicate | hasSocialMediaAccount |
P2943
|
FINISHED |
| Object | @wiumlie |
E12506
|
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: @wiumlie | Statement: [Håkon Wium Lie, hasSocialMediaAccount, @wiumlie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: @wiumlie Context triple: [Håkon Wium Lie, hasSocialMediaAccount, @wiumlie]
-
A.
@wiumlie
chosen
@wiumlie is the Twitter account of Håkon Wium Lie, the Norwegian web pioneer best known as the creator of Cascading Style Sheets (CSS).
-
B.
WU
WU is a leading European university in Vienna specializing in economics, business, and social sciences.
-
C.
WUG
WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
-
D.
WUH
WUH is the IATA airport code for Wuhan Tianhe International Airport, the main air gateway serving Wuhan in central China.
-
E.
LIM
LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc64e648190b9c4f980eb8168aa |
completed | March 1, 2026, 10:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac93d044bc819091fd0cfa7a957640 |
completed | March 7, 2026, 9:08 p.m. |
Created at: March 1, 2026, 7:50 p.m.