Triple
T19931867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S106 nebula |
E479072
|
entity |
| Predicate | hasCentralStar |
P104428
|
FINISHED |
| Object |
S106 IR
S106 IR is a massive young stellar object deeply embedded in the S106 nebula, whose intense radiation and stellar winds carve the nebula’s characteristic bipolar structure.
|
E1402529
|
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: S106 IR | Statement: [S106 nebula, hasCentralStar, S106 IR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S106 IR Context triple: [S106 nebula, hasCentralStar, S106 IR]
-
A.
IR-20
IR-20 is the ISO 3166-2 subdivision code assigned to Iran’s Semnan Province.
-
B.
S-102
S-102 is an IHO S-100 series standard that defines high-resolution bathymetric surface data for use in modern electronic navigation and marine applications.
-
C.
S-101
S-101 is the International Hydrographic Organization’s modern electronic navigational chart standard designed to support next-generation marine navigation systems.
-
D.
IR-13
IR-13 is the ISO 3166-2 subdivision code assigned to Iran’s Kurdistan Province.
-
E.
STH-106
STH-106 is a state highway in Wisconsin that serves as an east–west route connecting several communities in the southern part of the state.
- 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: S106 IR Triple: [S106 nebula, hasCentralStar, S106 IR]
Generated description
S106 IR is a massive young stellar object deeply embedded in the S106 nebula, whose intense radiation and stellar winds carve the nebula’s characteristic bipolar structure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: S106 IR Target entity description: S106 IR is a massive young stellar object deeply embedded in the S106 nebula, whose intense radiation and stellar winds carve the nebula’s characteristic bipolar structure.
-
A.
IR-20
IR-20 is the ISO 3166-2 subdivision code assigned to Iran’s Semnan Province.
-
B.
S-102
S-102 is an IHO S-100 series standard that defines high-resolution bathymetric surface data for use in modern electronic navigation and marine applications.
-
C.
S-101
S-101 is the International Hydrographic Organization’s modern electronic navigational chart standard designed to support next-generation marine navigation systems.
-
D.
IR-13
IR-13 is the ISO 3166-2 subdivision code assigned to Iran’s Kurdistan Province.
-
E.
STH-106
STH-106 is a state highway in Wisconsin that serves as an east–west route connecting several communities in the southern part of the state.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a13ebc08190a583aa4c5e9f6648 |
completed | April 20, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07f6e639788190a63c52cf284dbe99 |
completed | May 16, 2026, 4:47 a.m. |
| NEDg | Description generation | batch_6a07f7d235688190971c9c0063669470 |
completed | May 16, 2026, 4:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07f891e5c081909e30e9ce7c271359 |
completed | May 16, 2026, 4:54 a.m. |
Created at: April 10, 2026, 1:53 p.m.